Ranking Algorithm
Overview Search Engine Ranking Algorithms use data mining and inference techniques to rank content on the web. This ordered co ntent is what’s displayed on the results pages of search engines. Search engines incorporate a number of factors into their ranking algorithms to order content according to the relevancy of crawled information to each user. Critical factors for ranking algorithms include HTML tags, keyword density within a page, hyperlinks within, to and from a page, and sitemaps or webpage structure. A ranking algorithm assigns a numerical weight to online documents which act as a measure of usefulness and relevance to a search engine user. This is considered a measure of projected document importance to the user. Current Issues with Page Ranking Algorithms ---- Control in the Wrong Hands Ranking factors make it easy for content curators to manipulate page information to rank highly in the search engine results. This places too much control of search results in the hands of content creators. It places emphasis on writing for the purpose of ranking highly in the search engine results, instead of crafting content on the basis of the needs of site visitors. Search engines, such as Google, for instance, began penalizing those who incorporated blackhat techniques into their website. For instance, sites that once ranked highly for a decent keyword density were being ranked lowly. Search engines value authority sites that offer quality content but have not yet figured out the best way to incorporate that into their ranking algorithms. The internet is shifting to this idea of writing for people and not for search engines. Although search engines try to counteract these measures taken by content creators to get their sites and content indexed highly, the current method that search engines use to produce rank order for content importance is highly susceptible to manipulation. As the internet attempts to move forward to a semantic web, more emphasis will be placed on the content created and how this content is semantically structured, and not on how to manipulate a page’s internal links and backlinks along with HTML to rank highly. The ultimate goal is to keep shifting towards a web that best offers higher quality content that focuses on satisfying the needs of the user, is highly relevant and can do more for the user. The answer seems to lie in the idea behind a semantic web. Intellectual Isolation & Invasion of Privacy When a user provides access to their personal info, such as maintaining a search history or sharing their location data, algorithms can utilize this information to display customized results for every individual. Search engines incorporate this collected personal information into their ranking algorithms, in hopes of selecting information that is best suited and most relevant to the user. Very personalized search results come with its own set of issues, as users may unknowingly be providing their data to search engines, so their displayed results can be overly manipulated. This technique to make search personalized can be considered an invasion of privacy and creates what is known as the search or filter bubble phenomenon, which causes intellectual isolation. Although there is some control available to users to compensate for this, such as deleting or disabling browser cookies, anonymous web browsing or using a Virtual Private Network (VPN), users want more features incorporated into their internet experience to protect their data. References https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles Pariser, E. (2011). Eli Pariser: Beware Online" filter Bubbles". Ted. https://searchenginewatch.com/sew/news/2064539/how-search-engines-rank-web-pages Sullivan, D. (1997). How Search Engines Rank Web Pages. Search Engine Watch. Category:Search Engine Category:Ranking Category:Blackhat SEO Category:Modern Internet Technologies